%***********************************************************
% CS 229 Machine Learning
% Project - Kalman Smoother Wrapper
%-----------------------------------------------------------
% Completed by: Ching Yin Derek Pang
% Date : November 07, 2010
%***********************************************************

function xsmooth = ks(ynoise,F, H, Q, R, initX, initV)


%%-----------------------------------------------------------------------
% Noise simulation + Kalman smoother
%%-----------------------------------------------------------------------
%Model formulation with acceleration as input
% A = [1 1 1/2; 0 1 1; 0 0 1];
% %C = [1 0 0];
% 
% ss = 3; % state size
% os = 1; % observation size
% 
% %noise covariance matrix
% Q = qs*eye(ss);
% R = rs*eye(os);
% 
% %inital condition for x and covariance matrix
% initx = [0 0 0]';
% initV = 10*eye(ss);

%Apply Kalman smoother
[xsmooth, Vsmooth] = kalman_smoother(ynoise, F, H, Q, R, initX, initV);
